Land cover changes can impact many areas of life. These changes can affect deforestation, ecological communities, wildfire extent, and urban growth. This advanced series focuses on using satellite imagery to map changes in land cover. Attendees will learn change detection methods, including image subtraction and classification. They will also conduct their own change detection analysis. This training will use QGIS, the R statistical program, and the Random Forest algorithm. Both sessions will featured a lecture and hands-on exercises.

Read more about the image above at NASA Earth Observatory.

Objective

• Become familiar with Landsat bands and color combinations
• Understand how to visualize change in land cover using Landsat data
• Learn the basic steps for change detection by:
  • Conducting image subtraction between two dates using QGIS
  • Creating multi-date Landsat layer stacks
  • Conducting multi-date land cover classification using the Random Forest classification in R
  • Identifying and analyzing changes in land cover

Live sessions took place on 28 September-5 October 2018, but recordings are available.

Materials are available in English and Spanish.